用于近实时检测信用卡欺诈的Web服务

A. Tselykh, D. Petukhov
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引用次数: 6

摘要

本文的重点是设计和实现一个通过REST API访问的分布式、高度可扩展和容错的反欺诈服务。Web服务以接近实时的方式工作,并使用机器学习算法进行预测分析。我们的目标是开发一种负担得起的反欺诈服务,为参与各方(即商家、聚合代理、支付系统和银行)提供一种可能性,以降低其网站上欺诈支付的风险。我们探索了许多方法,这些方法大大减少了硬件和软件成本,并减小了项目团队的规模。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Web service for detecting credit card fraud in near real-time
This paper focuses on the design and implementation of a distributed, highly scalable, and fault-tolerant anti-fraud service accessible via REST API. Web service works in near real-time and employs machine learning algorithms for predictive analytics. Our goal is to develop an affordable anti-fraud service, which provides a possibility for participating parties (i.e. merchants, aggregating agents, payment systems, and banks) to reduce the risks of fraudulent payments over their sites. We explore a number of approaches resulting in a significant reduction of hardware and software costs as well as the size of the team working on the project.
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